Multiple objective branch and bound for mixed 0-1 linear programming: Corrections and improvements for the biobjective case

作     者：Vincent, Thomas Seipp, Florian Ruzika, Stefan Przybylski, Anthony Gandibleux, Xavier 

作者机构：Univ Nantes CNRS UMR 6241 LINA F-44322 Nantes 03 France Univ Kaiserslautern Dept Math AG Optimizat D-67663 Kaiserslautern Germany 

出 版 物：《COMPUTERS & OPERATIONS RESEARCH》 (计算机与运筹学研究)

年 卷 期：2013年第40卷第1期

页      面：498-509页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Nantes Metropole [ANR-09-BLAN-0361] Center of Mathematical and Computational Modeling of the University of Kaiserslautern Agence Nationale de la Recherche (ANR) [ANR-09-BLAN-0361] Funding Source: Agence Nationale de la Recherche (ANR) 

主　　题：Multi-objective mixed integer programming Nondominated set Dominance filtering Multi-objective linear programming Branch and bound 

摘      要：This work addresses the correction and improvement of Mavrotas and Diakoulaki s branch and bound algorithm for mixed 0-1 multiple objective linear programs. We first elaborate the issues encountered by the original algorithm and then propose a corrected version for the biobjective case using an exact representation of the nondominated set associated with an appropriate update procedure. Then we introduce several improvements using better bound sets and branching strategies and finally present some experiments to study the effectiveness of our propositions. (C) 2012 Elsevier Ltd. All rights reserved.